Plant Mol Biol (2012) 80:37–53 DOI 10.1007/s11103-011-9864-z
MicroRNAs in trees Ying-Hsuan Sun • Rui Shi • Xing-Hai Zhang Vincent L. Chiang • Ronald R. Sederoff
•
Received: 23 December 2010 / Accepted: 26 October 2011 / Published online: 8 December 2011 Ó Springer Science+Business Media B.V. 2011
Abstract MicroRNAs (miRNAs) are 20–24 nucleotide long molecules processed from a specific class of RNA polymerase II transcripts that mainly regulate the stability of mRNAs containing a complementary sequence by targeted degradation in plants. Many features of tree biology are regulated by miRNAs affecting development, metabolism, adaptation and evolution. MiRNAs may be modified and harnessed for controlled suppression of specific genes to learn about gene function, or for practical applications through genetic engineering. Modified (artificial) miRNAs act as dominant suppressors and are particularly useful in tree genetics because they bypass the generations of inbreeding needed for fixation of recessive mutations. The purpose of this review is to summarize the current status of information on miRNAs in trees and to guide future studies on the role of miRNAs in the biology of woody perennials and to illustrate their utility in directed genetic modification of trees.
Ying-Hsuan Sun, Rui Shi and Xing-Hai Zhang contributed equally. Y.-H. Sun R. Shi X.-H. Zhang V. L. Chiang R. R. Sederoff (&) Forest Biotechnology Group, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA e-mail:
[email protected] X.-H. Zhang Department of Biological Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA V. L. Chiang Department of Forest Biomaterials, North Carolina State University, Raleigh, NC 27695, USA
Keywords MicroRNA Woody plant Gene regulation Plant development Plant stress response Artificial microRNA
Introduction From the early evolution of woody plants and the formation of the first forests in the middle Devonian, about 385 million years ago (mya), trees have dominated terrestrial landscapes and the evolution of life on the land (Scheckler 2001). The major features of trees that distinguish them from their herbaceous relatives are the formation of wood, large size, and the perennial growth habit including the ability to establish dormancy (Samish 1954). The woody growth habit has been gained and lost many times during plant evolution. Early herbaceous plants quickly gave rise to trees and forests (Beck 1988), while the more recent evolution of herbaceous dicots arose from woody ancestors (Sinnott and Bailey 1915). Darwin (1859) remarked on the appearance of woody derivatives of herbaceous plants on island populations. DNA sequence relationships support the relatively recent evolution of woody plants found on islands descending from continental herbaceous founders (Bo¨hle et al. 1996; Helfgott et al. 2000). Woody plants and many herbaceous species show characteristic variation as they progress from a juvenile to a mature stage, a process known as phase change (Poethig 2010). The most apparent and most widely studied change is the ability to flower. Other components of phase change are leaf shape, phylotaxis, thorniness, pigmentation, and the rooting ability of cuttings (Robinson and Wareing 1969). Phase change is, at least in part, regulated by small RNAs (sRNAs) (Lauter et al. 2005; Baurle and Dean 2006; Wu et al. 2009, Wang et al. 2011).
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Trees must also be able to respond to extensive variation of biotic and abiotic stresses over long periods of time, in the extreme cases over thousands of years. Response to stress also involves miRNAs (Lu et al. 2005, 2008; Li et al. 2009; Jia et al. 2009a). Understanding the basis of stress responses is becoming more urgent as impending climate change increases threats to the world’s forests through changes in CO2, water and temperature and through increased susceptibility to pests and pathogens (Dale et al. 2001; Walther et al. 2002). The genetic model plant Arabidopsis, small, fast growing and herbaceous, can be induced to form woody tissue by delaying flowering and senescence (Lev-Yadun 1997). The changes in the regulation of a small number of genes may be the basis for the distinction between woody and herbaceous phenotypes (Groover 2005). Zhong et al. (2008) have characterized a suite of transcription factors that regulate secondary cell wall formation in Arabidopsis. Melzer et al. (2008) found that mutation of two Arabidopsis genes SUPPRESSOR OF CONSTANS (soc1-3) and FRUITFUL (ful-2), both MADS box transcription factors, was sufficient to create a woody phenotype.
Biogenesis and function of plant miRNAs RNA silencing in plants was first described by Napoli et al. (1990) by suppression of an endogenous gene by an exogenous transgene. The subsequent discovery that silencing was associated with sRNAs opened the door to a densely populated world of small interfering RNAs (siRNAs) (Hamilton and Baulcombe 1999). Plant sRNA silencing typically involves induction by double-stranded (ds)RNA, and the processing of the dsRNA into 18–25 nt molecules. These sRNAs are methylated at the 30 terminal nucleotide and incorporated into complexes that target RNA or DNA (Chapman and Carrington 2007). The most abundant sRNAs are siRNAs acting on repeated DNA in heterochromatin (Martienssen 2010; Jin and Zhu 2010) for transcriptional gene silencing (TGS). Long term stability of differentiation is particularly important in forest trees where active meristems for flowering and secondary growth are maintained for exceptionally long periods of time. Among the siRNAs are the miRNAs (Bartel 2004; Chapman and Carrington 2007; Jin and Zhu 2010). It has been 10 years since the first identification of functional miRNAs in plants (Reinhart et al. 2002; Park et al. 2002), which was 9 years after the first miRNA was discovered in Caenorhabditis elegans (Lee et al. 1993). These small heterogeneous molecules (20–24 nt) are endogenous sequence specific elements that mediate post transcriptional gene silencing (PTGS) (Voinnet 2009) and
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Fig. 1 Biogenesis and post transcriptional gene silencing of microRNAs in plants. In the nucleus (red box), miRNA genes are transcribed by RNA polymerase II (RNA pol II) to form primary miRNA (primiRNA) transcripts containing stem-loop structures. The pri-miRNAs are ‘‘diced’’ consecutively by dicer like protein 1 (DCL1) to produce pre-miRNAs and then the mature miRNA:miRNA* duplexes. MiRNA:miRNA* duplexes are transported into the cytoplasm (green box) where the mature miRNA enters into an RNA induced silencing complex (RISC). The miRNA guides the RSIC to the target site of the mRNA and induces mRNA cleavage and subsequent degradation
chromatin modification (Martienssen 2010; Jin and Zhu 2010). MiRNAs originate from long self-complementary transcribed precursors (pri-miRNAs) through multiple cleavage steps (by Dicer like enzymes) to form a short double strand duplex, and a mature miRNA (Fig. 1). Mature miRNAs are incorporated into an RNA-induced silencing complex (RISC) that negatively regulates gene expression by inhibition of translation or by cleavage of target mRNAs (Bartel 2004; Guo et al. 2005; Vazquez et al. 2010). The remaining complementary strand called miRNA* is degraded (Tomari et al. 2004). MiRNAs and siRNAs interact with target transcripts and guide mRNA cleavage. To some extent they share common pathways with other sRNAs for biogenesis and function (Allen et al. 2005; Voinnet 2009).
Origin and evolution of microRNAs MiRNA populations are characterized by both conservation and divergence. Plant and animal miRNAs share many similarities in structure and function although no specific miRNAs have been identified that are conserved between animals and plants (Ambros et al. 2003; Bartel 2004). Some miRNAs are conserved across vascular plants and mosses (Floyd and Bowman 2004; Axtell and Bartel 2005; TalmorNeiman et al. 2006). Alternatively, divergence can be rapid, and many miRNAs are lineage specific (Talmor-Neiman et al. 2006; Fahlgren et al. 2007; Barakat et al. 2007a).
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Fig. 2 Simplified phylogenetic relationships of major species of land plants discussed in this paper. The branch points of the evolutionary tree are based on the data obtained from Phytozome V 7.0 (http://www.phytozome.net) and Sederoff et al. (2009). Species that currently have miRNA sequences deposited in miRBase are presented in bold face font
Ancient (conserved) plant miRNAs preferentially target genes with roles in growth, development and differentiation while the less abundant and potentially younger miRNAs may have a more diverse set of functions (Zhang et al. 2006). MiRNAs have been studied in many species representing a wide diversity of taxa. Relatively few of these species are woody plants (Fig. 2; Table 1). The functions of miRNAs have been investigated by altering miRNA expression or by analyzing mutant target genes lacking miRNA binding sites (Wang et al. 2005; Wu and Poethig 2006; Liu et al. 2007). Models have been proposed for the origin of miRNAs (Voinnet 2009). Some pri-miRNAs have extensive similarity to the sequences of their target genes, as if they were generated by gene duplication (Allen et al. 2004; Fahlgren et al. 2007). Small random inverted repeats are widespread and many inverted repeats in transposable elements could readily form miRNA precursor-like stem loops (Piriyapongsa and Jordan 2008). MiRNAs are capable of many types of regulation in space and time. MiRNAs have an inherent potential for autoregulation of the abundance of its own full-length transcript. MiRNAs may have tissue and cell specific expression affecting development and differentiation in a great many ways. For example, HD-ZIP transcription factors are spatially regulated by miRNAs to direct leaf polarity in the embryonic meristem of Arabidopsis (Kidner and Martienssen 2004). The co-regulated expression of miRNA and its target may interact to stabilize fluctuating expression of a product as in the control of leaf margin
serration (Nikovics et al. 2006). Temporal expression of a miRNA can establish a gradient in leaf development in tomato (Ori et al. 2007). MiRNAs may also act at a distance, because RNA silencing in plants is not cell autonomous (Voinnet 2005). Some miRNAs may exert long distance functions through translocation by phloem to regulate phosphate or sulfur homeostasis (Pant et al. 2008; Kawashima et al. 2009).
MiRNA discovery in plants Plant miRNAs were discovered either by cloning and sequencing their transcripts from sRNA cDNA libraries (Llave et al. 2002), or by computational prediction of miRNA precursor structures within ESTs or whole genome sequence (Jones-Rhoades and Bartel 2004). Since the first discovery of miRNAs (Reinhart et al. 2002; Park et al. 2002), the guidelines to annotate miRNAs have evolved (Ambros et al. 2003; Meyers et al. 2008). The most recent guidelines (Meyers et al. 2008) include as a primary criterion, proof of precise excision from a stem-loop structure, and ancillary criteria such as evidence of conservation, targets and biogenesis. Advances in sequencing technology have greatly accelerated sRNA discovery (Lu et al. 2006; Heisel et al. 2008; Simon et al. 2009) as well as the assembly of genomes and transcriptomes for plant miRNA identification. High throughput sequencing has also allowed the verification of miRNA target cleavage sites on
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NA
NA
Populus tremula (aspen)
Populus tremula x Populus alba
NA
NA
Leaves, vegetative buds, weekly in June and July
Young but fully expanded leaves
Cloning and sequencing
Cloning and sequencing
Cold, drought, hydration, salinity
Cloning and sequencing
Populus balsamifera (balsam poplar)
Developing xylem
Cloning and sequencing
Populus trichocarpa (black cottonwood)
Library source of miRNAs
Methods for miRNA discovery
Species
Table 1 Summary of miRNA studies in tree species
NA
NA
MiRNA filter array for ABA and salt response Association of wood formation and expression of Pta-miR166 and PtaHB1
NA
NA
NA
miR1448: Putative disease resistance protein
miR1446: GCN5-related N-acetyltransferase (GNAT) family protein, Gibberellin response modulator-like protein
miR1444: Polyphenol oxidase
miR482: Putative disease resistance protein
miR482: Putative disease resistance protein
miR480: Proton-dependent oligopeptide transport protein
miR479: Unknown protein
miR478: Organic anion transporter-like protein
miR477: GRAS domain–containing protein
miR476: PPR
miR474: PPR, Kinesine, Leucine-rich repeat protein miR475: PPR
miR473: GRAS domain–containing protein
miR408: Plastocyanin-like, Early-responsive to dehydration-related protein
Experimentally verified miRNA targets
MiRNA filter array for UVB response
Leaves and vegetative buds
Genome wide profiling of small RNAs
Whole plants
Leaves, phloem, xylem, tension xylem and opposite xylem
Tissues, treatments or materials assayed
Ko et al. (2006)
Jia et al. (2009b)
Jia et al. (2009a)
Barakat et al. (2007b)
Klevebring et al. (2009)
Lu et al. (2008)
Lu et al. (2005)
Reference
40 Plant Mol Biol (2012) 80:37–53
1 year old green house grown tissues 1 year old green house grown tissues
NA
Cloning and sequencing
Cloning and sequencing
Populus x canadensis
Populus euphratica (European poplar)
NA
NA
NA
Populus tremula x Populus alba (Hybrid aspen)
Library source of miRNAs
Methods for miRNA discovery
Species
Table 1 continued
Dehydration
Dehydration
NA
Vascular tissue development in trees transformed with an altered POPCORONA (a Class III HD ZIP) resistant to miR166 suppression and an amiRNA specific to POPCORONA Phase change in miR156 overexpressed transgenic trees
peu-miR93: NADH-ubiquinone dehydrogenase, transcript of unknown function
peu-miR84*: Transcript of unknown function
peu-miR71*: Transcript of unknown function peu-miR77: Transcript of unknown function
Peu-miR67*: Golgi snare 11, methionine aminopeptidase
peu-miR58: SPL transcription factor
peu-miR30: Transcript of unknown function
peu-miR131: SPL transcription factor
peu-miR123: DCD (Development and Cell Death) domain protein
Peu-miR106*: Cytochrome c oxidase biogenesis protein peu-miR115: Ribosomal protein L2 family
peu-miR101: MYB transcription factor
miR1444: Tyrosinase
miR482: NB-ARC domain-containing disease resistance protein
miR166: Homeobox transcription factor
miR164: NAC domain transcription factor
miR156: SPL transcription factor, transcript of unknown function miR159: MYB transcription factor
NA
NA
NA
Experimentally verified miRNA targets
Vascular tissue development in trees transformed with an altered popREVOLURA (a Class III HD ZIP) resistant to miR166 suppression
Tissues, treatments or materials assayed
Li et al. (2011)
Li et al. (2009)
Wang et al. (2011)
Du et al. (2011)
Robischon et al. (2011)
Reference
Plant Mol Biol (2012) 80:37–53 41
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123 89 various EST libraries
EST libraries from various tissues
Flower buds, partially and fully opened flowers, developing fruit
Cloning and sequencing
Computational (based on ESTs)
Computational (based on ESTs)
miR-RACE and computational (based on ESTs and miRBase)
Cloning and sequencing
Eucalyptus grandis
Citrus reticulata (mandarin orange)
Poncirus rifoliate (trifoliate orange), also called Citrus rifoliate
NA
NA
Young and old leaves, young stem, flower bud, flower and developing fruits
Computational (based on ESTs and miRBase)
NA
Computational (based on ESTs and miRBase) and miR-RACE
Malus domestica (apple)
Fruit pulp of wild type and red-flesh mutant
Cloning and sequencing
Citrus sinensis (sweet orange)
89 various EST libraries
Xylem, phloem and leaf
Salt stress of six month old plants in tissue culture
Cloning and sequencing
Populus cathayana
Library source of miRNAs
Methods for miRNA discovery
Species
Table 1 continued
Young and old leaves, young stem, flower bud, flower and developing fruits
Periderm, phloem and xylem
Flower buds, fruit at various times after full bloom, leaves and roots
Stem-loop qRT-PCR or PCR for miRNA abundance in wild type and red-flesh mutant
NA
Roots, leaves, young shoots, flowers and fruit (1 cm diameter)
Roots, stems and leaves
Leaves, young shoots, flowers and fruit (1 cm diameter)
Abundance in xylem, phloem and leaf
Salt stress
Tissues, treatments or materials assayed
NA
NA
miR398: Superoxide dismutase
miR156: SPL transcription factor
NA
ctr-miRn4: NB-LRR disease resistance protein
ctr-miRn3: NB-LRR disease resistance protein
ctr-miRn2: NB-LRR disease resistance protein
miR397: Laccase (IRX12)
miR1446: GRAS family transcription factor resistance protein
miR482: NB-LRR disease resistance protein
miR319: TCP transcription factor
miR171: SCL transcription factor
miR167: Auxin response factor (ARF)
miR164: NAC domain transcription factor
miR394: F-box protein miR156: SPL transcription factor
miR393: Transport inhibitor response-like protein (TIR)
miR167: Auxin response factor (ARF)
miR160: Auxin response factor (ARF)
NA
NA
NA
Experimentally verified miRNA targets
Yu et al. (2011)
VarkonyiGasic et al. (2010)
Gleave et al. (2008)
Xu et al. (2010)
Song et al. (2010b)
Song et al. (2010a)
Song et al. (2009)
Song et al. (2009)
Victor (2006)
Zhou et al. (2011)
Reference
42 Plant Mol Biol (2012) 80:37–53
miR-RACE and computational (based on ESTs and miRBase)
Computational (based on castor bean genome and miRBase)
Prunus persica (peach)
Ricinus communisi (Caster bean)
NA
Pinus resinosa (red pine)
NA
Young needles
NA
Cloning and sequencing
NA
Cloning and sequencing
Pinus taeda (loblolly pine)
Pinus contorta (lodgepole pine)
Developing xylem of 1-year-old green house plants
Computational (based on ESTs and miRBase)
NA
NA
EST libraries from various tissues
Library source of miRNAs
Camellia sinensis (tea tree)
Jatropha curcas (Jatropha tree)
Manihot esculenta (Cassava)
Hevea brasiliensis (rubber tree)
Methods for miRNA discovery
Species
Table 1 continued
MiRNA array analysis of mature needles
Northern and qRT-PCR for abundance in zygotic embryos and female megagametophytes
Healthy stems, rust galls, gall stems, stems above galls, needles and roots
NA
Abundance in various Euphorbiaceae species and response to abiotic stresses including cold and drought.
Leaves, flower buds and fruit at various developmental stages
Tissues, treatments or materials assayed
miR172: APETALA2-like transcription factor
NA
NA
miR951: Non-protein coding gene
miR950: Non-protein coding gene
miR949: Transcripts of unknown function
miR948: Serine/threonine kinase
miR947: Non-protein coding gene
miR946: Disease resistance protein
miR160: Auxin response factor (ARF)
mIR159: MYB transcription factor
miR156: SPL transcription factor, transcript of unknown function
NA
NA
miR393: Transport inhibitor response-like protein (TIR)
miR156: SPL transcription factor, LIGULELESS protein
miR164: NAC domain containing transcription factor
miR160: Auxin response factor (ARF)
NA
Experimentally verified miRNA targets
Axtell and Bartel (2005)
Morin et al. (2008)
Oh et al. (2008)
Lu et al. (2007)
Prabu and Mandal (2010)
Zeng et al. (2010)
Zhang et al. (2011)
Reference
Plant Mol Biol (2012) 80:37–53 43
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Computational (based on miRBase and ESTs)
Pinus pinaster (maritime pine)
NA
Cloning and sequencing
Larix leptolepis (Japanese larch)
Taxus chinensis (Chinese yew)
NA information not available
Cloning and sequencing
Picea abies (Norway spruce)
Picea sitchensis (sitka spruce)
Picea engelmannii x P. sitchensis
Picea glauca (white spruce)
Methods for miRNA discovery
Species
Table 1 continued
Methyl jasmonate treatment of cell lines
NA
Shoots from epigenetically responsive and epigenetically indifferent seedlings
NA
Library source of miRNAs
MiRNA abundance profiles of methyl jasmonate treatment of cell lines
MiRNA microarray analysis of embryonic and non-embryonic callus
MiRNA abundance profiles of seedlings at LD or SD for 6 or 20 days
NA
Tissues, treatments or materials assayed
NA
NA
NA
NA
Experimentally verified miRNA targets
Qiu et al. (2009)
Zhang et al. (2010)
Yakovlev et al. (2010)
Zhang et al. (2006)
Reference
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a transcriptome-wide scale (German et al. 2008; AddoQuaye et al. 2008). Full genomic sequences are available for Populus trichocarpa, Eucalyptus grandis, apple (Malus domestica) and peach (Prunus persica) (Phytozome 7.0: http://www.phytozome.org/; http://eucalyptusdb.bi.up.ac.za/). Several sequencing projects are in progress for other tree species, such as Chinese chestnut (Castanea mollissima; http://www.fagaceae.org), loblolly pine (Pinus taeda), and Norway spruce (Picea abies). Studies of miRNA function in plants have focused on miRNA expression during development or under stress (Palatnik et al. 2003; Chen 2004; Sunkar and Zhu 2004; Guo et al. 2005; Sunkar et al. 2006; Lu et al. 2005, 2007, 2008). MiRNA discovery in trees has also followed similar areas of interest. Work on trees has included horticultural tree species and several forest trees (Table 1). The distinction between woody and herbaceous species is to some extent arbitrary. We have included some horticultural species in this review, but not some perennials such as Vitis spp.
MiRNAs in Populus spp. Poplars are fast growing forest tree species with a relative small genome size (*450 Mbp), and a relatively short time to reach reproductive maturity (Ridge et al. 1986; Bradshaw et al. 2000; Stokstad 2006; Tuskan et al. 2006). Poplars were targeted as model forest species for genetic and ecological research (Taylor 2002; Wullschleger et al. 2002; Brunner et al. 2004; Tuskan et al. 2004). Populus species have potential for applications in carbon sequestration and for lignocellulosic energy feedstocks (Tuskan 1998; Bradshaw et al. 2000; Tuskan and Walsh 2001; Wullschleger et al. 2002, 2005). Therefore, a plurality of the forest tree miRNA studies today have been carried out on Populus (Table 1). Sunkar and Zhu (2004) first discovered three poplar miRNAs (miR397a, miR403 and miR408) by the similarity of sequences with known stem-loop structures of cloned Arabidopsis miRNAs. From the P. trichocarpa genome annotation (Tuskan et al. 2006), 169 gene loci of 21 P. trichocarpa miRNA families were computationally predicted based on the sequences of miRNAs in rice and Arabidopsis. By combining small RNA cloning, computational stem-loop evaluation and target authentication using 50 RACE (rapid amplification of cDNA ends), Lu et al. (2005, 2008) expanded the list of P. trichocarpa miRNAs to 234 loci in 42 families. Barakat et al. (2007b) obtained reads of small RNAs using 454 sequencing of sRNAs derived from leaves and vegetative buds of Populus balsamifera collected over a growing season. By comparing the P. balsamifera sRNAs
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to the P. trichocarpa genome, 47 new candidate miRNA families were identified, although putative targets were not experimentally confirmed. Five miRNAs of 4 families were discovered in Populus euphratica by sRNA cloning and stem-loop structures were inferred from a limited set of ESTs (Li et al. 2009). A total of 239 miRNA genes from 46 miRNA families are annotated for poplars in the current miRBase (Release 17; http://www.mirbase.org/). The first systematic discovery of poplar miRNAs (P. trichocarpa) was reported by Lu et al. (2005). By cloning the sRNAs collected from developing secondary xylem of 2-year-old trees, 22 miRNAs of 21 families were discovered. Twelve of the families were either identical or very similar to Arabidopsis miRNAs, the remaining 10 miRNAs in P. trichocarpa were novel. The target genes of these novel miRNAs were computationally predicted and experimentally confirmed by 50 RACE. Unlike the conserved miRNAs that target transcription factors, most of the confirmed target genes of novel miRNAs are involved in transport, protein modification, signal transduction or encode defense related leucine-rich repeat (LRR) or pentatricopeptide repeat (PPR) proteins. The exceptions are Ptc-miR473 and Ptc-miR477 that target GRAS domaincontaining transcription factors (Bolle 2004). Tissue expression profiles of the identified miRNAs using either gel blots or quantitative real-time PCR (qRT-PCR) showed a pattern that is different from their Arabidopsis homologs. The majority of the miRNAs also showed differential expression patterns in different tissues as well as in developing xylem subjected to bending (mechanical stress), suggesting that these miRNAs are associated with tension wood formation. From P. trichocarpa 1.5-month-old rooted cuttings subjected to cold, heat, drought, water, salinity, and mechanical stress, Lu et al. (2008) identified 68 additional miRNAs of 27 families. Among these miRNA families, 17 ptc-miRNAs are conserved between poplar and Arabidopsis; and one (miR530) was also found in rice. Seven families (miR1444 to 1450) were newly discovered and specific to P. trichocarpa. The identities of the experimentally confirmed target genes of these 7 newly discovered miRNA families include LRR proteins in defense or signal transduction (miR1448), polyphenyl oxidase (miR1444), gibberelin response modulator-like protein and GCN5-related N-acetyltransferase (miR1446). From miRNA microarray and qRT-PCR results, 16 miRNA families were found to respond to cold stress. Target gene functions of these miRNAs are known to be involved in plant development and stress responses. Some miRNA members within the same family had different responses to cold stresses. Some miRNAs are also involved in both biotic and abiotic stresses. The cross-talk among different stress
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response miRNAs suggests that a miRNA regulatory network exists for stress responses. P. euphratica is a model for studies of abiotic stress because it is highly resistant to high salt, high temperature, and drought. Because miRNAs have been associated with stress responses (Lu et al. 2008; Jia et al. 2009a), miRNAs in P. euphratica were evaluated for their drought response (Li et al. 2009). From an sRNA library, 54 miRNAs of 14 families were identified. The qRT-PCR results indicated that 5 miRNAs were differentially expressed during drought in 1-year-old trees. Li et al. (2011) further investigated the miRNA response to drought stress by high throughput sequencing combined with microRNA microarray analysis. The results identified 58 new miRNAs of 38 families including one located in an intron (mirtron). 21 target genes for 14 newly identified miRNAs were verified by PARE (parallel analysis of RNA ends) sequencing of partially degraded transcripts (degradome analysis). 23 miRNAs conserved between P. trichocarpa and P. euphratica were identified as differentially expressed during drought stress, with 9 down-regulated and 14 up-regulated. Response to ABA and salt stress was investigated in Populus tremula and compared to Arabidopsis (Jia et al. 2009b). In P. tremula, over 15 abundant miRNAs were shown to be differentially expressed and similarly regulated by ABA and salt. Most of them were induced after short-term stress while two were suppressed. ABA and high salt induced the transient expression and accumulation of miR398 in P. tremula while similar treatment in Arabidopsis resulted in opposite responses (Jia et al. 2009b). Jia et al. (2009a) also evaluated the response of P. tremula miRNAs to UV-B stress in 1.5 month-old plantlets. By using a spotted filter array, a total of 24 miRNAs in 16 families were found to respond to UV-B. Nine miRNA families were up regulated and 7 were down regulated. 145 target genes were predicted for these UVBresponsive miRNAs. These target genes fall into three functional categories: signal cascades, transcription factors, and metabolism. Transcript abundance for some of these target genes was negatively correlated with the increase in abundance of the miRNAs in response to UV-B. Light and stress responsive cis-elements were prevalent in the 2,500 bps upstream of the predicted pre-miRNAs in P. trichocarpa for the 8 major UV-B responsive miRNA encoding genes. Taken together, the results (Jia et al. 2009a; Li et al. 2009) support the hypothesis of Lu et al. (2008) that there is cross-talk among different stress responses through miRNAs. In the stem of hybrid poplars (Populus tremula 9 Populus alba) miR166 is inversely correlated with the expression of its target PtaHB1 gene and the growth of secondary xylem (Ko et al. 2006). PtaHB1 encodes a class III HD-ZIP protein, a plant specific transcription factor
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involved in epidermal and vascular differentiation. The transcript abundance of PtaHB1 is closely associated with secondary growth and varies seasonally. Ko et al. (2006) suggested that miR166 plays a role in regulating the annual growth cycle and may have important implications for seasonal adaptation of trees. A hybrid aspen (P. tremula 9 P. alba) class III HD-ZIP ortholog of the Arabidopsis gene REVOLUTA was made resistant to the suppression induced by miR166 by artificial mutation of the miRNA target site in the HD-ZIP sequence (Robischon et al. 2011). The transgenic plants carrying this mutation showed abnormalities affecting both primary and secondary growth. Abnormalities include formation of cambia within cortical parenchyma and secondary vascular tissue in reverse polarity (phloem inside of xylem) (Robischon et al. 2011). The HD-ZIP and the miRNA appear to control early events in vascular tissue development. Similarly, another class III HD-ZIP gene, a hybrid aspen ortholog of the Arabidopsis gene CORONA, was shown to be involved in secondary growth of woody stems (Du et al. 2011). An artificial miRNA specifically suppressing the target HD-ZIP (POPCORONA) resulted in abnormal lignification in pith, while overexpression of a miR166 resistant form of POPCORONA resulted in delayed lignification in xylem and phloem fibers. The juvenile-mature phase change appears to be regulated by miRNAs in both herbaceous and woody plants. In Arabidopsis, miR156 maintains juvenility by down regulating SPL (SQUAMOSA PROMOTER BINDING PROTEIN-LIKE) transcription factors (Wu et al. 2009; Poethig 2010). Wang et al. (2011) have shown that overexpression of miR156 in Populus 9 canadensis, reduced the expression of the target gene SPL and miR172, and drastically prolonged the juvenile phase. The abundance and stability of some miRNAs may be regulated by polyadenylation and exosome-mediated degradation. Lu et al. (2009) studied miRNAs in three meristmatic tissues (shoots, roots and cambial meristems) in P. trichocarpa using high throughput sequencing. They discovered that many miRNAs are polyadenylated and that they may be polyadenylated to different extents. For example, 72% of miR1450, 63% of miR1447, and 35% of miR397 were polyadenylated in shoot, root and cambial meristem tissues combined. The extent of polyadenylation and truncation of miRNAs differs among these different tissues.
MiRNAs in Eucalyptus The only report of miRNAs in Eucalyptus (Victor 2006) described sRNAs isolated from xylem, phloem and leaves
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of Eucalyptus grandis. Twenty miRNAs of 5 families known in other plants and 28 novel miRNAs of 8 families were identified. Using the Arabidopsis and poplar genomes as reference, 110 target transcripts covering a wide range of functions were computationally predicted. qRT-PCR analysis revealed that miRNAs of 11 families were expressed at various levels in both the xylogenic and nonxylogenic tissues. MiRNA egr-miR90 showed high specificity for leaves while egr-miR359 was detected only in phloem. The genome sequence of Eucalyptus grandis has been completed (Eucalyptusdb, http://eucalyptusdb.bi.up. ac.za/) and should be released in near future, providing an important new resource for miRNA discovery and comparative functional analysis.
MiRNAs in citrus Several studies have reported on miRNAs from other economically important tree species (Table 1). The first citrus miRNAs were identified by Song et al. (2009) who found homologs in citrus ESTs for 27 miRNAs known in Arabidopsis. Various degrees of tissue and species specific expression of these miRNAs were observed for leaves, young shoots, flowers, fruit and roots of Citrus reticulata (mandarin orange) and Poncirus trifoliata (trifoliate orange). Based on sequence complementarity, 41 potential targets were predicted for 15 miRNAs, and 4 of these targets were verified by mapping their cleavage sites with 50 RACE. More recently, Song et al. (2010a) analyzed 9 of the previously studied miRNAs from P. trifoliata by RACE and verified their expression patterns. In addition, 8 putative targets for 7 miRNAs were mapped by 50 RACE. In a separate study (Song et al. 2010b), high throughput sequencing was used to analyze an sRNA library generated from P. trifoliata flowers and fruit. Sixty-three sequences of 42 highly conserved miRNA families were identified. Ten novel miRNAs were discovered and their expression in roots, stems, leaves, flower buds, open flowers and fruit was assayed by qRT-PCR. Putative targets were predicted for 24 of the conserved miRNA families and 3 of the novel miRNAs. Four of the predicted targets were experimentally verified. Likewise, Xu et al. (2010) constructed sRNA libraries from fruit of a red flesh bud sport (somatic mutant) and its wild type in sweet orange (C. sinensis). High throughput sequencing identified 85 known miRNAs (48 families) and 12 novel miRNAs. Comparative profiling of the sequence reads found significant expression differences between mutant and wild type for 51 known miRNAs and 9 novel miRNAs. A total of 418 target genes were computationally predicted. These results show a high degree of pleiotropy from a bud sport mutation and suggest a novel role of miRNAs in carotenoid biosynthesis.
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MiRNAs in apple Three studies of apple miRNAs have been reported (Table 1). By analyzing EST databases, Gleave et al. (2008) identified 7 conserved miRNA families. Northern blots confirmed the presence of these miRNAs in apple tissues. Some miRNAs were expressed constitutively in all tissues examined (flower buds, fruits, leaves from fungusinfected seedlings, tissue culture plantlets and roots), while others were preferentially expressed in different tissues or were induced by fungal infection. EST sequences of potential targets were found for 6 miRNA families. Cleavage of two of the target mRNAs was verified by 50 RACE. Similarly, Yu et al. (2011) re-analyzed the augmented apple EST databases and identified 31 miRNAs belonging to 16 families. Sixteen conserved miRNAs (one from each family) were validated by miR-RACE and qRT-PCR. Like their orthologs in poplar and Arabidopsis, many of these 16 miRNAs were expressed in all tissues tested (young and old leaves, young stem, flower buds, flowers and developing fruit), while others exhibited tissue or growth stage specific expression. Fifty-six potential targets were identified including several transcription factor mRNAs. Expression of 12 of these targets was quantified by qRT-PCR. Among the 21 apple miRNAs examined by northern blotting and in situ hybridization (Varkonyi-Gasic et al. 2010), 18 were expressed in at least one of the tissues examined (shoot apex, leaf, stem, periderm, phloem and xylem); 17 of them were found in phloem. At least 8 widely expressed miRNAs were also detected in sieve elements and phloem sap, suggesting long-distance signaling. A negative correlation between 6 miRNAs and their target mRNAs was revealed by RT-PCR. Long range signaling may be a particularly important function of miRNAs in trees.
MiRNAs in peach Peach is emerging as a woody plant genomic model for the Rosaceae (Zhebentyayeva et al. 2008). It has a small genome size (*225 Mbp) and the sequence has been recently completed (http://www.phytozome.org). From the sequence database of 80,857 ESTs, 22 potential miRNAs of 7 families were predicted (Zhang et al. 2011). Using miR-RACE PCR, 8 candidate miRNAs were sequence verified and found to have diverse tissue specific expression patterns.
MiRNAs in tea, rubber tree and Jatropha We are aware of only one report of miRNAs from tea (Camellia sinensis) where 4 miRNAs were identified based
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on sequence conservation (Prabu and Mandal 2010). Thirty targets of various functions were computationally predicted. Zeng et al. (2010) examined miRNAs in 4 Euphorbiaceae species including rubber tree (Hevea brasiliensis) and Jatropha tree (Jatropha curcas). Expression of 39 miRNAs was assayed by RT-PCR in Jatropha tree and rubber tree.
MiRNAs in gymnosperms Gymnosperms are fundamentally different from angiosperms in seed formation and flowering (Beck 1988). Because of the widespread roles of miRNAs as gene regulators, miRNAs may be associated with gymnospermunique processes of differentiation and development. Recent work on gymnosperm miRNAs has focused on discovery and functional analysis (Table 1). Whole genome sequence is not yet available for any gymnosperm, however, large numbers of ESTs have been collected (Kirst et al. 2003; Pavy et al. 2007; Ralph et al. 2008) and have facilitated miRNA discovery. Axtell and Bartel (2005) used array hybridization to detect homologs of Arabidopsis miRNAs in many plant species, including red pine (Pinus resinosa). Half of the conserved miRNA families detected were expressed in pine needles. Based on ESTs, Zhang et al. (2006) identified a limited number of conserved miRNAs in several species of Pinaceae, including the spruce hybrid Picea engelmannii 9 P. sitchensis, white spruce (Picea glauca), sitka spruce (Picea sitchensis), maritime pine (Pinus pinaster) and loblolly pine (Pinus taeda). More recently, several groups have identified a large number of conserved and novel miRNAs from gymnosperm sRNA libraries (Lu et al. 2007; Morin et al. 2008; Qiu et al. 2009; Yakovlev et al. 2010). Based on the current miRNA registration database (miRBase Release 16.0), *70 miRNA families have been recognized in gymnosperms, including several families that appear to be specific to gymnosperms. For example, miR946, miR947 and miR950 were confirmed in both Norway spruce and loblolly pine, but not in any angiosperm species. Small RNAs of 21 nt (including miRNAs) are the dominant sRNA species in lodgepole pine (Pinus contorta) (Morin et al. 2008; Dolgosheina et al. 2008) and Chinese yew (Taxus chinensis) (Qiu et al. 2009). In angiosperms, 24 nt sRNAs are more abundant and are known to guide DNA methylation and heterochromatinization (Matzke et al. 2007; Martienssen 2010). Conifers have a novel dicer-like protein (DCL) but lack the enzyme DCL3 that matures 24 nt sRNAs in angiosperms (Dolgosheina et al. 2008). The fact that conifers do not produce significant amounts of 24 nt sRNAs suggests that gymnosperms and angiosperms
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have different biogenesis pathways for sRNAs. The relationship of 24 nt sRNAs and heterochromatinization could be related to sequence redundancy and suggests a potential mechanism for the evolution of the unusually large gymnosperm genomes (Ahuja and Neale 2005). As in angiosperms, gymnosperm miRNAs may be associated with specific developmental stages or responses to abiotic or biotic stresses. Lu et al. (2007) identified loblolly pine miRNAs associated with gall formation after infection of seedlings by the fusiform rust fungus Cronartium quercuum f. sp fusiforme. The expression of 10 of 11 identified miRNA families was significantly repressed in the galled stems compared to the healthy control samples, suggesting the involvement of these miRNAs in the host-pathogen interaction. Oh et al. (2008) presented evidence of seed developmental stage and tissue specific modulation by some miRNAs in loblolly pine. During embryogenesis, the transcript of the HB15L gene, targeted by miR166, can be cleaved in both zygotic embryos and female gametophytes, while the transcript of the ARF8L gene targeted by miR167 was only cleaved in zygotic embryos. Using microarray and qRT-PCR analyses, Zhang et al. (2010) identified 4 differentially expressed miRNAs from 165 miRNAs examined in embryogenic and non-embryogenic callus of Japanese larch (Larix leptolepis). They found that miR171 was significantly up regulated in embryogenic callus, and miR159, miR169 and miR172 were down regulated compared to non-embryogenic cultures. Analyses of their target genes implicated these miRNAs as important regulators of embryogenesis. Methyl jasmonate treatment of Chinese yew cultured cells induced the production of taxoids, a family of diterpenes that include the antitumor drug Taxol (paclitaxel). Members of at least 9 miRNA families were significantly affected (Qiu et al. 2009). However, these miRNAs do not target known genes in the paclitaxel pathway. Perhaps they function at a more general level of metabolic processes, rather than a taxoidcommitted biosynthetic pathway. Tissue culture cells are quite different from the bark tissues that accumulate paclitaxel, therefore, more research is needed. Yakovlev et al. (2010) studied epigenetic effects of warm and cold environments on developing seeds of Norway spruce. Sixteen of the 44 miRNAs identified were expressed differently in full-sib families showing distinct epigenetic differences in bud set associated with temperature treatment of the seed.
Genetic manipulation of trees through artificial miRNAs Using a human miRNA, Zeng et al. (2002) found that alteration of a miRNA sequence within its precursor does
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not affect its biogenesis if the hairpin-loop structure is not disturbed. This result led to the creation of artificial miRNAs (amiRNA) that act on specific targets (Parizotto et al. 2004; Alvarez et al. 2006; Niu et al. 2006; Schwab et al. 2006). AmiRNAs reduce the abundance of gene transcripts containing a complementary sequence. Web-based resources have been developed to aid in plant amiRNA design, such as WMD3 (Schwab et al. 2006; http://wmd3. weigelworld.org/). The amiRNA sequence is then integrated into a modified miRNA precursor within a functional miRNA transcript. This amiRNA precursor can be inserted into a transformation vector and introduced into plants for expression. Similar to the native miRNAs (Fig. 1), amiRNAs can be processed to their mature forms and direct the RISC to down regulate the target genes (Fig. 3). For plant species where whole genomes have been sequenced, it is possible to avoid off-target suppression by selecting an amiRNA sequence that can distinguish between closely related genes. The amiRNA technique is of great value in functional genomics for tree species because amiRNAs act as
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dominant suppressors in the first generation of plant transformation. By contrast, recessive mutations require subsequent inbreeding to generate homozygotes. AmiRNAs have been shown to be effective in Populus (Du et al. 2009), where similar homologs within a gene family can be discriminated and specifically suppressed (Shi et al. 2010). Du et al. (2009) adopted the amiRNA technique to down regulate a homeobox gene ARBORKNOX2 (ARK2) in hybrid aspen (P. alba 9 P. tremula). They designed an amiRNA sequence and integrated it into an Arabidopsis MIR164b precursor for repression of ARK2 following transfer into aspen. Their analysis showed that amiRNA transgenics are more stable and efficient than those created by RNA interference (RNAi). Ptr-miR408 from P. trichocarpa was modified for amiRNA suppression of PAL genes (Shi et al. 2010). Two amiRNAs (amiRNA-palA and amiRNA-palB) were designed to target two highly similar subsets of PAL genes (subset A includes PAL2, 4, and 5 while subset B includes PAL1 and 3). The amiRNAs were expressed in transgenic trees and specifically down regulated their target PAL genes without off-target effects on other PALs. Specific down regulation of PAL gene subset A by amiRNA-palA led to an increase in transcript abundance of subset B. The reciprocal effect by amiRNA-palB was not observed. The ability of amiRNAs to specifically down regulate closely related genes is important for functional analysis of gene redundancy found in tree species.
Discussion and conclusions
Fig. 3 Construction of an artificial miRNA (amiRNA) gene for plant transformation. A 21 nt sequence (amiRNA, green bar) and its near perfect complement (miRNA*, purple bar) are computationally designed based on the mRNA target sequence of interest (black bar). These two DNA sequences (green bar and purple bar) replace the miRNA (red bar) and miRNA* (blue bar) sequences respectively in a selected plant miRNA gene while keeping the rest of the gene sequence unchanged. The resulting amiRNA transgene is inserted into a transformation vector and introduced into plant cells. Expression of the amiRNA transgene leads to miRNA biogenesis and specific mRNA degradation as described in Fig. 1
Today, the major outlines of the functional interactions of plant miRNAs are becoming known (Voinnet 2009). While large numbers of sRNAs, many of them miRNAs, have been identified in trees, only small numbers have verification of function. There is great value to be gained from a comparative approach across both major and minor taxa. There are many examples of plants that have made a transition between woody and herbaceous growth habits, particularly in island populations that have undergone rapid recent evolution (Bo¨hle et al. 1996). There is evidence of both conservation and lineage specific evolution in gymnosperms and angiosperms. While there is apparent similarity of machinery for processing, recognition, splicing and silencing, differences in mechanisms of sRNA biogenesis between angiosperms and gymnosperms exist. Dolgosheina et al. (2008) demonstrated an absence of DCL3 transcripts in lodgepole pine, and a dearth of the 24 nt sRNAs that DCL3 acts upon during maturation. Instead, a novel dicer like family was detected. MiRNAs act as both regulators and targets of transcription factors. As mentioned earlier, a miRNA
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developmental switch regulates the juvenile-mature phase change. MiR156 maintains plant juvenility by down regulating SPL transcription factors. The SPL transcription factors act on miR172b that regulates AP2 (APETALA2) factors that act as negative regulators of adult phenotypes (Wu et al. 2009; Poethig 2010). A similar control system appears to function in maize (Lauter et al. 2005). The regulatory conservation between Arabidopsis and maize appears to extend to at least to some forest trees (Wang et al. 2011). MiRNAs also regulate the vegetative-reproductive transition (flowering). The expression of miR156 delays flowering while miR172 has an opposite effect. MiRNA 172 acts through relieving FT (FLOWERING LOCUS T) repression of flowering in Arabidopsis (Mathieu et al. 2009; Fornara and Coupland 2009). Another target of miR172 is SMZ (SCHLAFMUTZE), an AP2-like transcription factor that controls FT. Overexpression of miR156 acting through repression of SPL transcripts delays activation of FUL and SOC1. FUL and SOC1 accelerate flowering, whereas the double mutant of ful-2 and soc1-3 converts Arabidopsis from an herbaceous to a woody state (Melzer et al. 2008). Similar interactions, presumably important for the perennial growth habit, have not yet been demonstrated in trees. Vernalization is the acquisition of the ability to flower following a cold winter period acting on either seeds or whole plants. In Arabidopsis, flowering locus C (FLC) is involved in control of vernalization (Lin et al. 2005; Wang et al. 2009). A close relative of Arabidopsis, Arabis alpina, is a perennial that undergoes plant vernalization. A mutation in the A. alpina FLC ortholog (pep1) perpetuates flowering (Wang et al. 2009). In Arabidopsis, FLC normally acts to inhibit flowering until exposed to winter temperatures that stably repress FLC transcription (Wang et al. 2009). MiRNA families 172 and 156 are induced and constantly expressed respectively, by cold treatment, and are therefore linked to the temperature response pathway and the control of flowering (Zhou et al. 2008; Lee et al. 2010). How these mechanisms affect flowering in trees remains to be investigated. It has been suggested that some miRNAs may be transported by phloem to regulate phosphate or sulfur homeostasis in Arabidopsis and common bean (Pant et al. 2008; Kawashima et al. 2009; Liu et al. 2010). While it is clear there is long distance signaling of phosphate deficiency, miR399 has been proposed as a long distance signaling molecule. Many other miRNAs have been found in abundance in phloem sap of apple (Varkonyi-Gasic et al. 2010) supporting the notion of long distance movement of miRNA in trees. The greatest gap in our knowledge remains in the unknown functions of the majority of genes in plants particularly tree species. Future miRNA studies in trees will
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likely be directed to finding functions for genes, and dissecting functional redundancy. MiRNAs and amiRNAs are powerful tools for basic research and for genetic modifications. MiRNA based technology will allow the specific down regulation of a great many genes of unknown function. Using gene specific suppression with miRNAs or amiRNAs, it is possible to distinguish functions of redundant genes. Genetic manipulation or engineering of new miRNAs could allow the specific regulation of candidate genes for modification of metabolism, growth, development, and adaptation of trees. Such modifications would advance breeding programs in horticulture and forestry, and improve wood properties, energy content, conversion efficiency for biofuels, or response to climate change. Acknowledgments This work is supported in part by the National Research Initiative of the USDA Cooperative State Research, Education and Extension Service (CSREES) #2006-35504-17233 to VLC. X.-H.Z. wishes to thank the Chiang laboratory for hosting his sabbatical leave. We are grateful to Jack Wang for drawing Figs. 1 and 3.
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